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In this case, usually, Normalization is done. For example in your training and testing data, you need the same shape, so that you should try something like, mean = np.mean(X_train_features, axis=0) std = np.std(X_train_features, axis=0) X_train_features = (X_train_features - mean)/std Here X_train_features can be a data frame of spectrogram or mfcc features....


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